Application of PSO in LCMV Beamforming Technique - Darzi, Soodabeh;Tariqul Islam, Mohammad;Sieh Kiong, Tiong
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The current book attempts to investigate the application of Particle Swarm Optimization (PSO) in the Linear Constraint Minimum Variance (LCMV) beamforming technique that improves the signal to interference and noise ratio, data rates, null steering and coverage of the cellular system. LCMV forms its radiation beam towards desired signal through its weight vectors which are computed through received signal. However, weights computed by LCMV usually do not able to form the radiation beam towards the target user precisely. Hence, in this research work, PSO is incorporated into the existing LCMV technique in order to improve the weights of LCMV.…mehr

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Produktbeschreibung
The current book attempts to investigate the application of Particle Swarm Optimization (PSO) in the Linear Constraint Minimum Variance (LCMV) beamforming technique that improves the signal to interference and noise ratio, data rates, null steering and coverage of the cellular system. LCMV forms its radiation beam towards desired signal through its weight vectors which are computed through received signal. However, weights computed by LCMV usually do not able to form the radiation beam towards the target user precisely. Hence, in this research work, PSO is incorporated into the existing LCMV technique in order to improve the weights of LCMV.
Autorenporträt
Soodabeh Darzi is a PhD candidate and researcher in Department of Electrical Engineering at university Kebangsaan Malaysia (National University of Malaysia).